Our goal is to create a choropleth of the confirmed cases by state. We would like to use layers to show the progression over time. So we will have a different layer for each point in time. Specifically, we will want 4 layers, one for June 1st, August 1st, October 1st, and December 1st.

We will also want to add a layer that allows us to toggle on/off plotting of county borders.

Take 3-5 minutes to identify what major data wrangling steps need to take place in order for this to work.

If you get stuck, visit the leaflet guide https://rstudio.github.io/leaflet/. For help with a specific function use the ? function to read the help documentation.

# Use this R-Chunk to import all your datasets!
#covid now contains the cumulative confirmed case count by county for every day since the start of the pandemic
covid <- read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_US.csv")


#These two files read in sf objects that contain the geometry of the counties and states respectively
counties <- USAboundaries::us_counties() %>%  dplyr::select(-9) %>%  #Removing the 9th column because it has the same name as another column, 'state_name'
  filter(state_name != "Alaska" & state_name != "Hawaii" & state_name != "Puerto Rico")
state48 <- USAboundaries::us_states() %>%  
  filter(name != "Alaska" & name != "Hawaii" & name != "Puerto Rico")

Data Wrangling

Step through each data verb/line of code to understand what it is doing and why. Fill in the blanks so that the code will run correctly.

covid_states_long <- covid %>% filter(Province_State %in% state.name) %>% 
  #recall that state.name is a vector of the names of the United States that comes built in to base R.
  dplyr::select(Province_State, `1/22/20`, `1/23/20`, `1/24/20`, `1/25/20`) %>% 
  group_by(Province_State) %>% 
  summarise(Dec = sum(`1/22/20`),
            Jun = sum(`1/23/20`),
            Aug = sum(`1/24/20`),
            Oct = sum(`1/25/20`)) %>% 
  pivot_longer(cols = c(Dec, Jun, Aug, Oct), values_to =  "cases", names_to = "when")

Note the use of pivot_longer() above. The data needs to be in long form in order for the layering to work easily

The goal of this next line of code is to get the state boundaries geometry contained in state48 into the same data set as the long-form covid data.

covid_lay_long <- inner_join(covid_states_long, state48, by = c("Province_State" = "name"))

Plotting the data

Our dataset is ready for plotting. We will now set the stage/prepare/define the colors to be used in the choropleth. Ensure you understand each piece of the code and fill in the blanks so that it runs correctly.

#Create a color palette to assign colors to the various values
pal <- colorNumeric(palette = c("white", "orange", "red"),
                    domain = min(covid_lay_long$cases):max(covid_lay_long$cases))

We will now create the plot and add a control box to allow the viewer to control which layer they want to see.

leaflet() %>% 
  setView(lng = -99, lat = 40, zoom = 4) %>% 
  addProviderTiles(providers$Esri.NatGeoWorldMap) %>%
  
  addPolygons(data = st_as_sf(filter(covid_lay_long, when == "Jun")),
              group = "Jun",
              fillOpacity = .5,
              fillColor =  ~pal(cases)) %>% 
  addPolygons(data = st_as_sf(filter(covid_lay_long, when == "Aug")),
              group = "Aug",
              fillOpacity = .5,
              fillColor = ~pal(cases)) %>% 
  addPolygons(data = st_as_sf(filter(covid_lay_long, when == "Oct")),
              group = "Oct",
              fillOpacity = .5,
              fillColor = ~pal(cases)) %>% 
  addPolygons(data = st_as_sf(filter(covid_lay_long, when == "Dec")),
              group = "Dec",
              fillOpacity = .5,
              fillColor = ~pal(cases)) %>% 
  addLayersControl(
    baseGroups = c("Jun", "Aug", "Oct", "Dec"),
    options = layersControlOptions(collapsed = FALSE))

After getting the above code running by filling in the blanks. Answer these questions:

  • What does st_as_sf() do, and why is it necessary?
    • Could I have avoided the need to use st_as_sf()?
  • What happens when you change the collapsed = FALSE argument to true?

Adding toggle on/off layer(s)

Now we want to add the option to toggle on/off a layer of county borders.

myleaflet <- leaflet() %>% 
  setView(lng = -99, lat = 40, zoom = 4) %>% 
  addProviderTiles(providers$Esri.NatGeoWorldMap) %>%
  
  addPolygons(data = st_as_sf(filter(covid_lay_long, when=="Jun")),
              group = "Jun",
              fillOpacity = .5,
              fillColor = ~pal(cases)) %>% 
  addPolygons(data = st_as_sf(filter(covid_lay_long, when == "Aug")),
              group = "Aug",
              fillOpacity = .5,
              fillColor = ~pal(cases)) %>% 
  addPolygons(data = st_as_sf(filter(covid_lay_long, when == "Oct")),
              group = "Oct",
              fillOpacity = .5,
              fillColor = ~pal(cases)) %>% 
  addPolygons(data = st_as_sf(filter(covid_lay_long, when == "Dec")),
              group = "Dec",
              fillOpacity = .5,
              fillColor = ~pal(cases)) %>% 
  #This next layer is the county shape outlines
  addPolygons(data = counties, weight = 1,
              group = "counties",
              fill = FALSE, 
              color = "black") %>% 
  addLayersControl(
    baseGroups = c("Jun", "Aug", "Oct", "Dec"),
    overlayGroups = "counties",
    options = layersControlOptions(collapsed = FALSE))

myleaflet

Think about it. If you wanted to add another layer to toggle on/off (say for example, state capitals), do you know how to do it? Describe the necessary steps / change in code to your group to a group member or friend.

Adding a legend

We start with the plot created with above code, stored in myleaflet. Fill in the blanks to add a legend that will show the meaning/scale of the color coding.

myleaflet %>% 
    addLegend(position = "topright", pal = pal, values = covid_lay_long$cases,
            title = "Cumulative Confirmed Covid Cases",
            #labFormat = labelFormat(suffix = "%"),
            opacity = 1)